-
NTIRE 2019 Challenge on Video Deblurring: Methods and Results
AbstractThis paper reviews the first NTIRE challenge on video deblurring (restoration of rich details and high frequency components from blurred video frames) with focus on the proposed solutions and results. A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed dynamic motion blurs while Track 2 had additional MPEG video compression artifacts. Each competition had 109 and 93 registered participants. Total 13 teams competed in the final testing phase. They gauge the state-of-the-art in video deblurring problem.
Related Material
[pdf][bibtex]@InProceedings{Nah_2019_CVPR_Workshops,
author = {Nah, Seungjun and Timofte, Radu and Baik, Sungyong and Hong, Seokil and Moon, Gyeongsik and Son, Sanghyun and Mu Lee, Kyoung},
title = {NTIRE 2019 Challenge on Video Deblurring: Methods and Results},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
These CVPR 2019 workshop papers are the Open Access versions, provided by the Computer Vision Foundation.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
This material is presented to ensure timely dissemination of scholarly and technical work.
Copyright and all rights therein are retained by authors or by other copyright holders.
All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.